| 1 |
머신 러닝과 데이터 전처리를 활용한 증류탑 온도 예측
이예찬, 최영렬, 조형태, 김정환
Korean Chemical Engineering Research, 59(2), 191, 2021 |
| 2 |
A comparison of multiple methods for mapping local-scale mesquite tree aboveground biomass with remotely sensed data
Ku NW, Popescu SC
Biomass & Bioenergy, 122, 270, 2019 |
| 3 |
A data-centric predictive control approach for nonlinear chemical processes
Wang RG, Bao J, Yao YC
Chemical Engineering Research & Design, 142, 154, 2019 |
| 4 |
Long-term forecast of energy commodities price using machine learning
Herrera GP, Constantino M, Tabak BM, Pistori H, Su JJ, Naranpanawa A
Energy, 179, 214, 2019 |
| 5 |
TG-FTIR and Py-GC/MS analyses of pyrolysis behaviors and products of cattle manure in CO2 and N-2 atmospheres: Kinetic, thermodynamic, and machine-learning models
Zhang JH, Liu JY, Evrendilek F, Zhang XC, Buyukada M
Energy Conversion and Management, 195, 346, 2019 |
| 6 |
Large-scale rooftop solar photovoltaic technical potential estimation using Random Forests
Assouline D, Mohajeri N, Scartezzini JL
Applied Energy, 217, 189, 2018 |
| 7 |
Data-driven model predictive control using random forests for building energy optimization and climate control
Smarra F, Jain A, de Rubeis T, Ambrosini D, D'Innocenzo A, Mangharam R
Applied Energy, 226, 1252, 2018 |
| 8 |
Random Forests for mapping and analysis of microkinetics models
Partopour B, Paffenroth RC, Dixon AG
Computers & Chemical Engineering, 115, 286, 2018 |
| 9 |
Detection of under deposit corrosion in a CO2 environment by using electrochemical noise and recurrence quantification analysis
Hou Y, Aldrich C, Lepkova K, Kinsella B
Electrochimica Acta, 274, 160, 2018 |
| 10 |
Identifying corrosion of carbon steel buried in iron ore and coal cargoes based on recurrence quantification analysis of electrochemical noise
Hou Y, Aldrich C, Lepkova K, Kinsella B
Electrochimica Acta, 283, 212, 2018 |
